You Don’t Buy AI-Powered Tech—You Hire It

There are a thousand business owners waiting for artificial intelligence to “arrive,” in a commercial sense.

They see AI’s potential, and they’re waiting for it to evolve into a product that can actually affect their business in a positive way, not just play board games.

What they don’t realize is commercial AI is already here.

If commercial AI is already available and ready to contribute meaningfully to businesses, then why aren’t there more early adopters? Because adopting AI doesn’t just require you to reconfigure your company’s stack, it requires you to rethink how you implement technology in general.

Business owners are having a hard time seeing the value AI could bring their company right now because they are thinking of AI-powered tech in comparison to other software purchases, when they really need to approach AI as a new hire.

Why Artificial Intelligence Isn’t An Overnight Solution

When you bring a new hire onto your company, their full impact is never felt right away. In fact, as you will know if you’ve ever hired a new assistant, a new hire can actually bring down productivity in their first week. Onboarding takes time.

However, as a new hire’s responsibilities become clearly defined, and they gain the information needed to execute in their role autonomously, they become a major asset to your team.

Artificial intelligence works the same way.

Your technology has to learn the exact scope of its responsibilities. If you’re handing off your initial customer service to a AI-powered virtual assistant, it must learn all sorts of things before it can contribute meaningfully:

Who should it be engaging and who should it escalate to human support?

What are the bounds of its acceptable responses?

At what point is it acceptable to end the conversation?

And so much more. Just like a new hire needs plenty of experience before having a real effect on your company, new AI needs a massive data set before it can really contribute.

But AI Can Revolutionize Your Business In One Year

When Google’s AlphaGo beat Lee Sedol, one of the best Go players in the world, it marked a high-water moment for AI. Go, the oldest board game in history, has more possible configuration of pieces than there are atoms in the observable universe.

Up until now, that intense complexity has resisted algorithmic solution. While computers decades ago mastered games like chess—there are computer-only chess leagues where every “participant” is far better than the best human player—Go wasn’t supposed to be conquered for at least another ten years when AlphaGo famously defeated Sodol.

That actually maps well to what AI in a business setting looks like. On the day you implement AI, it will be no where near where you want it to be. However, as it learns, it will quickly outpace your predictions for its value.

Banks and other companies in the financial sector have made this realization, giving to the rise of the various AI-powered virtual assistants employed by companies like Bank of America and MasterCard.

Why You Can’t “Wait For AI To Improve”

In the traditional enterprise software model, once a technology is customized and implemented, its value quickly becomes apparent. It is only after implementation that traditional technology decreases in value, as newer technology is developed.

Artificial intelligence flips this model completely. AI-powered technology is at its least valuable the day it is implemented. The technology only becomes valuable to a business once it has had time to learn and be trained for the business’ specific use-case.

While tech insiders have a habit of making very optimistic predictions when it comes to the timelines for new technology, the opposite holds true for AI. Right now, the general consensus is that AI is years away from real consumer products.

In late March, Microsoft’s VP of Research Peter Lee openly said that powerful machine learning technology wasn’t realistic as a product yet, because it requires too much labor and tailoring to the end-user’s needs.

When AI-powered technology is ready to make an impact on businesses on its first day of implementation, the thinking goes, it will be a commercially viable product.

The problem with that is this: artificial intelligence may never be an out of the box solution for businesses. It’s simply not how it works. Artificial intelligence—and machine learning in particular—represents an entirely new way of thinking about technology in business.

Like any key hire, AI can do very little for your company on Day 1, but by Day 365, it can completely revolutionize your business.

Waiting for AI to “arrive” only extends the time until your particular technology is trained and ready to contribute, and by taking that extra time, you’re giving your competition time to pull ahead.